Best Relational Databases and Database Tools for 2026

Relational databases are the most common way to store and manage data. They organize information into structured tables with rows and columns, defining relationships between different entities. This structured approach ensures data integrity, consistency, and efficient querying across all industries, from small businesses to enterprises, and both on-premises and in the cloud.

This article explores the leading relational databases, their features, capabilities, and everyday use cases. Also, it highlights comprehensive relational database tools from the popular Devart's dbForge product line, including SQL Server tools, MySQL tools, Oracle tools, and PostgreSQL tools for performing all database-related tasks across these major platforms.

Devart dbForge - best tools for relational databases

Many professionals prefer third-party database tools for greater flexibility, especially when working across multiple databases in environments that combine cloud and on-premises systems. One of the most powerful and popular options in this area is Devart's dbForge product line:

• dbForge Edge - A multi-featured solution for major RDBMSs (SQL Server, MySQL/MariaDB, Oracle, and PostgreSQL/Amazon Redshift) and a wide range of cloud services. Edge enables users to handle all stages of database development, management, analysis, and administration.
• dbForge Studios - Standalone IDEs for individual RDBMSs: dbForge Studio for SQL Server, dbForge Studio for MySQL, dbForge Studio for Oracle, and dbForge Studio for PostgreSQL. Each Studio provides a full toolset for SQL coding, comparing and synchronizing databases, generating test data, data migration, analysis, and reporting, and much more.
• dbForge tools - Specialized standalone applications for specific tasks within particular database systems, such as dbForge SQL Tools, a bundle of 15 essential tools for SQL Server specialists.
• dbForge AI Assistant - An integrated AI-powered assistant that helps speed up SQL coding by generating, optimizing, and troubleshooting SQL queries.

Among the key advantages of dbForge, it is worth focusing primarily on its powerful visualization and automation capabilities.

• Intuitive visual interface - A user-friendly GUI allows you to configure tasks visually using convenient wizards, reducing the need for manual SQL coding and minimizing human errors. Visual features like query building, schema and data comparison, data import and export, database monitoring, and user management all benefit from this visual approach, making routine but demanding tasks faster and easier to perform.
• Ease of use - dbForge tools are accessible even to users without deep SQL expertise. At the same time, experienced database professionals appreciate the speed and efficiency provided by the GUI-driven workflow.
• CLI-powered automation - dbForge tools enable users to automate, schedule, and execute repetitive tasks automatically. This option saves time, increases consistency, and supports DevOps processes.

The dbForge product line delivers everything developers, administrators, and other database professionals need for efficient database management. Whether working with a single database type or managing complex, multi-database or hybrid environments, dbForge provides the tools to meet every requirement with speed, accuracy, and reliability.

What is a relational database?

Relational databases are built on the relational model, organizing stored data into tables composed of rows and columns. Each row represents a unique entity, while each column defines a specific attribute or characteristic of that entity. A key feature of relational databases is their ability to establish relationships between tables using primary and foreign keys. These relationships keep the data structured and organized, allowing users to work with it efficiently.

Besides, relational database management systems (RDBMSs) provide a wide range of features that support application development. Their compliance with ACID principles (Atomicity, Consistency, Isolation, and Durability) guarantees that all transactions are safe and reliable, and query optimization mechanisms help improve database performance.

At the core of every RDBMS is SQL (Structured Query Language), the standard language for interacting with databases that uses declarative syntax. It allows developers to specify what they want to achieve, while the database system determines how to execute it. With SQL, users can create, modify, and delete database objects, as well as query and manipulate data.

Let us explore some of the most popular RDBMS solutions designed to meet the needs of different types of businesses.

Top relational databases for enterprises

An enterprise business is a large, complex organization often engaged in commercial, industrial, or professional activities. These businesses typically have a substantial workforce, extensive resources, and usually operate across multiple countries. Common examples include banks, insurance companies, healthcare systems, and logistics providers.

Enterprise database systems must meet stringent requirements. They need to handle massive volumes of data (often billions of records) while managing highly complex data structures. In addition, they must support the creation and execution of numerous stored procedures and ensure reliability, scalability, regulatory compliance, and high availability to keep mission-critical operations running smoothly. Several options on the market satisfy such requirements.

Oracle Database

Oracle Database is a world-leading relational database management system, highly regarded for its enterprise-grade performance and reliability. It is often the preferred solution for large-scale, complex projects that require robust transaction handling, advanced security, and seamless scalability. Oracle also offers strong capabilities in cloud computing and data warehousing, making it suitable for modern enterprise environments.

Key features

• High availability and disaster recovery (Oracle Real Application Clusters and Data Guard)
• Data partitioning and optimization tools
• Data security with Transparent Data Encryption, fine-grained access control, and audit vault
• Multitenant architecture with pluggable databases (PDBs)
• Data compression and storage efficiency mechanisms
• In-database analytics and machine learning capabilities
• Spatial and graph data management

Best for

• Government and public sector solutions
• Healthcare and insurance systems
• Online transaction processing (OLTP) environments
• Cloud-based enterprise platforms
• AI-driven data analysis and processing

Pros

• Enterprise-level functionality, reliability, and performance
• Comprehensive data protection and security features

Cons

• Steep learning curve
• High licensing and operational costs

Pricing

• Oracle Database Standard Edition 2 (SE2) - $17,500 per processor (or $350 per Named User Plus)
• Oracle Database Enterprise Edition (EE) - $47,500 per processor (or $950 per Named User Plus)
• Oracle Database Personal Edition - $460 per Named User Plus (user licenses Personal Edition; no processor licensing)

Microsoft SQL Server

Microsoft SQL Server is a robust relational database management system developed and maintained by Microsoft. It is widely adopted in corporate and enterprise environments, particularly where high transaction volumes, complex business analytics, and strict data security are required. SQL Server stands out for its in-memory performance, integrated business intelligence (BI) tools, and deep integration with the Microsoft ecosystem, including Windows Server, Azure, and Power BI.

Key features

• Scalability through clustering, partitioning, and parallel query processing
• Data integration and transformation with SQL Server Integration Services (SSIS)
• Business reporting and visualization with SQL Server Reporting Services (SSRS)
• Analytical processing and data mining with SQL Server Analysis Services (SSAS)
• Data security through encryption, authentication, and access control mechanisms
• High availability via AlwaysOn Availability Groups and failover clustering
• Full-text indexing and advanced search capabilities

Best for

• Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems
• Financial services and auditing applications
• Healthcare and government systems that require secure data management
• Data warehousing and business intelligence platforms integrated with Power BI and SSAS
• E-commerce and SaaS platforms supporting high-volume online transaction processing (OLTP)

Pros

• Integration with Microsoft products and cloud services
• High performance for complex queries and analytical workloads
• Flexible deployment across on-premises and cloud environments

Cons

• Primary optimization for the Windows environment
• High licensing and operational costs

Pricing

• Free - Express, Developer
• Paid - Standard server ($989), Standard per core ($3,945), Enterprise ($15,123)

Amazon RDS

Amazon RDS (Relational Database Service), offered by Amazon Web Services (AWS), is a fully managed service for deploying and maintaining relational databases in the cloud. Rather than being a standalone database engine, it provides an automated environment for managing popular SQL engines, including MySQL, PostgreSQL, MariaDB, Oracle, and Microsoft SQL Server.

Amazon RDS automates time-consuming administrative tasks, such as provisioning, backups, patching, and scaling, so that organizations can focus on application development rather than database maintenance.

Key features

• Multi-database support (MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server)
• Read replication for performance and scalability through read-only replicas
• Storage flexibility with General Purpose (SSD), Provisioned IOPS (SSD), and Magnetic options
• Monitoring and performance tracking via Amazon CloudWatch metrics
• High availability through Multi-AZ (Availability Zone) deployment
• Data security with encryption at rest and in transit using AWS Key Management Service (KMS)

Best for

• Enterprise applications such as ERP, CRM, and internal tools
• Data warehousing and analytics for small to mid-scale workloads
• Applications managing large streams of device-generated data
• Compliance and security-sensitive applications in industries like healthcare and finance

Pros

• Broad feature set with multiple supported database engines
• Automated patching and maintenance
• Automated backups, point-in-time recovery, and snapshot management
• Seamless integration with other AWS services
• Simplified scaling and disaster recovery
• No hardware maintenance or manual server management

Cons

• Limited scalability and sharding support
• Higher cost for advanced configurations and storage options
• Slower node addition due to data copying requirements
• No horizontal scaling (scale-out) for write operations
• Downtime required for specific scaling actions
• Lack of automated performance tuning

Pricing

Flexible, depends on many factors, such as DB engine, instance type and size, AWS Region and AZ, services chosen, etc.

Google Cloud SQL

Google Cloud SQL is a fully managed relational database service provided by Google Cloud Platform (GCP), with support for the most widely used database engines: MySQL, PostgreSQL, and SQL Server. Google Cloud SQL automates administrative tasks such as provisioning, patching, backups, and scaling.

At the same time, the integration with GCP services like Compute Engine, Kubernetes Engine (GKE), App Engine, and BigQuery makes this system ideal for cloud-native applications, analytics, and enterprise workloads.

Key features

• High availability with automatic failover, regional replication, and SLA-backed uptime
• Scalability through vertical and horizontal scaling
• Automated backups, point-in-time recovery, and encrypted backup storage
• Security and compliance with major industry standards (ISO, PCI DSS, HIPAA)
• Monitoring and logging via Cloud Monitoring and Cloud Logging
• Migration and import/export tools, including DMS and standard SQL utilities
• Regional and multi-zone deployment for disaster recovery and fault tolerance
• Developer-friendly management through Cloud Console, gcloud CLI, Terraform, and API endpoints

Best for

• Data analytics and reporting integrated with BigQuery and Dataflow
• Enterprise applications, including inventory management, CRM, and financial systems
• Microservices architectures, supporting independent databases and scalable deployments
• Development and testing environments with quick provisioning

Pros

• Easy setup and user-friendly interface
• Automated encryption, backups, and failover for business continuity
• Deep integration with the GCP ecosystem and APIs for easy access
• Flexible pricing with pay-as-you-go, sustained-use, and committed-use discounts
• Automated task management, including storage, updates, and redundancy

Cons

• Higher cost as database usage scales
• Limited database engine support
• Interface and configuration can be confusing
• Reduced customization and advanced configuration options

Pricing

Flexible, depending on the services chosen. The provider offers a system calculator to approximately estimate the fees.

Best open-source relational databases

Open-source databases are systems whose source code is publicly available. Unlike proprietary databases, they allow accessing and customizing the source code to meet specific needs and sharing improvements with the broader community.

While open-source databases are typically free to use, many have evolved significantly over the years, offering advanced features, reliability, and performance. This maturity has driven their widespread adoption across organizations of all sizes.

PostgreSQL

PostgreSQL is an open-source object-relational database management system (ORDBMS) known for its extensibility, reliability, and SQL standards compliance. It supports advanced data types, complex queries, and modern data-handling capabilities, making it ideal for a wide range of workloads, from web applications to large-scale data analytics.

Key features

• Extensive data type support, including arrays, JSONB, and user-defined types
• Advanced concurrency through Multiversion Concurrency Control (MVCC)
• Foreign Data Wrappers (FDW) for querying external data sources
• Full-text search and indexing capabilities
• Table partitioning and inheritance for structured data management
• Logical and streaming replication for scalability and fault tolerance
• Security mechanisms, including SSL, Role-Based Access Control (RBAC), and row-level security
• Extensible architecture supporting custom functions, data types, and procedural languages
• High performance and optimization features

Best for

• Financial systems requiring transactional integrity and complex queries
• Geospatial databases using the PostGIS extension for spatial data processing
• Web applications for high-performance and dynamic content management
• Scientific databases handling large-scale research and analytical data
• Data warehousing and analytics workloads with advanced query capabilities

Pros

• Free, open-source, and cross-platform
• Highly extensible and standards-compliant
• Strong community and long-term development support
• High customization and integration with external systems

Cons

• Complex performance tuning requires expertise
• Limited optimization for huge enterprise workloads

Pricing

Free, open-source

MySQL

MySQL, owned by Oracle Corporation, is one of the world's most popular open-source relational database management systems. With its speed, reliability, and ease of use, MySQL takes top positions as a choice for web applications, e-commerce platforms, and data-driven services. It offers high performance for heavy workloads and is often used by small and medium-sized businesses, startups, and large-scale web services alike.

Key features

• Scalability via replication, sharding, and clustering mechanisms
• Multiple storage engines for flexible data management
• Support for triggers, stored procedures, and views
• Advanced security features, including encryption and access control
• JSON support for semi-structured data
• Various replication configurations for high availability and fault tolerance
• Compatibility with popular development stacks such as LAMP (Linux, Apache, MySQL, PHP/Python/Perl)

Best for

• Web-based applications requiring fast and reliable data management
• E-commerce platforms managing product catalogs, transactions, and user data
• Data warehousing and reporting solutions
• Logging and monitoring applications handling large data volumes efficiently
• Content management systems (CMS) supporting dynamic content and user interactions

Pros

• Free, open-source platform with active community support (and commercial editions available)
• High performance and efficiency for read-heavy operations
• Comprehensive security configuration
• Flexible replication and clustering options for improved availability
• Strong JSON support and compatibility with modern development tools

Cons

• Limited optimization for very large or complex enterprise workloads
• Complex setup and configuration for large-scale deployments
• Lacks native graph and advanced analytics capabilities compared to competitors
• Performance and scalability limitations under heavy write-intensive workloads

Pricing

• Free: Community license
• Paid: Standard Edition ($2,000 per server per year), Enterprise Edition ($5,000 per server per year)

MariaDB

MariaDB is a community-driven, open-source relational database management system created by the original developers of MySQL. It was designed as a drop-in replacement for MySQL, and now it maintains full compatibility with it, introducing additional performance, scalability, and security enhancements. MariaDB offers a flexible architecture with multiple storage engines, advanced indexing, and robust query optimization, thus becoming a reliable and high-performance solution for modern data-driven applications.

Key features

• Enhanced query optimization on complex queries and large datasets
• Multiple storage engines, including Aria (transactional), ColumnStore (analytical), and MyRocks (high-performance)
• Advanced replication features such as multi-source replication and parallel replication
• Full compatibility with MySQL, ensuring smooth migration and application interoperability
• Extensive indexing options, including B-tree, hash, and full-text indexes
• Flexible deployment options across on-premises, cloud, and hybrid infrastructures

Best for

• E-commerce platforms requiring scalable and reliable transactional databases
• Web applications that demand consistent performance and compatibility
• Data warehousing for analytics, reporting, and historical data management
• Cloud-based applications integrating with public or private cloud environments

Pros

• Open-source and community-driven with transparent development
• Full compatibility with MySQL
• Strong security features, including encryption and user access control
• Flexible storage engine architecture for diverse workloads
• High performance and reliability for transactional and analytical applications

Cons

• Potential compatibility issues with applications explicitly built for MySQL
• Limited support for certain advanced enterprise features (e.g., partitioning, materialized views)

Pricing

Free, open-source

SQLite

SQLite is a self-contained, file-based, open-source RDBMS known for its portability, reliability, and simplicity. It operates without a server process, allowing applications to read and write directly to a single database file on disk. This lightweight design makes SQLite ideal for embedded systems, mobile apps, and local data storage in resource-constrained environments.

Despite its compact size, SQLite provides ACID-compliant transactions and strong SQL feature support, ensuring data integrity and stability even in cases of crashes or power loss.

Key features

• Zero-configuration operation with no server setup or administration required
• Single-file database storage for easy portability and file transfer
• Lightweight architecture suitable for embedded systems and mobile devices
• Full-featured SQL implementation supporting most of the SQL92 standard
• High reliability and minimal external dependencies

Best for

• Embedded databases in mobile applications and software tools
• Local storage for desktop applications and offline data management
• Unit testing and prototyping for database-driven projects
• Devices that require small, efficient local data storage
• Small to medium-sized websites managing lightweight user and content data

Pros

• Minimal footprint (often under 600 KiB) and self-contained design
• Cross-platform compatibility across Windows, macOS, Linux, and Android
• Simple setup with no server processes, configuration, or administration required
• Full portability (a database in a single file, easily shared or moved)
• Reliable, crash-resistant, and ACID-compliant

Cons

• Limited concurrency: only one process can write to the database at a time
• No built-in user or access management system
• Weaker security model compared to client-server RDBMSs
• Not suitable for large-scale, high-traffic, or multi-user enterprise environments

Pricing

• Free, open-source
• Paid options for personalized technical support

Lightweight and affordable RDBMS for small businesses

In addition to popular open-source databases such as MySQL, MariaDB, PostgreSQL, and SQLite, several other relational databases are commonly used by small businesses. Their main advantages lie in intuitive data representation and ease of access. Let's take a closer look at these options as well.

Firebird

Firebird is an open-source, lightweight relational database management system known for its compact size, minimal setup, and low resource consumption. Based on the SQL standard and fully ACID-compliant, Firebird offers an efficient solution for applications that require reliability and portability without the overhead of large enterprise systems. It requires little administrative effort and is well-suited for embedded, industrial, and transactional applications.

Key features

• Support for stored procedures and triggers via PSQL (Procedural SQL)
• Enforcement of referential integrity through foreign keys
• Extensibility with user-defined functions (UDFs) for custom logic
• Complete cursor implementation in PSQL for advanced data operations
• An incremental backup system to minimize downtime and storage use
• Variety of database access methods (API, ODBC, JDBC, .NET, Python, PHP, Perl)
• Rapid data recovery without the need for separate transaction logs
• Broad ecosystem of third-party administration and replication tools

Best for

• Industrial process analysis in real time
• Point-of-sale (POS) systems with local transaction management
• Handling customer data, billing, and rate calculations
• Document management systems
• Gaming backends maintaining persistent game states

Pros

• Minimal resource consumption ideal for low-performance or embedded environments
• Fast setup and easy installation requiring minimal configuration
• Low administrative overhead with self-managing features and simple deployment
• Active community, extensive support, and documentation
• Excellent cross-platform compatibility

Cons

• Limited horizontal scalability
• Single-server deployment model
• Fixed schema structure with predefined tables and columns
• Complex management and maintenance of stored procedures over time

Pricing

Free, open-source

CockroachDB

CockroachDB is a distributed SQL database designed to withstand hardware, network, and even data center failures with minimal operational overhead. CockroachDB combines the familiarity of SQL with the elasticity and fault tolerance of cloud-native systems, offering strong consistency through the SERIALIZABLE isolation level, the strictest standard in SQL.

Its architecture is inspired by Google Spanner but is open-source and easier to deploy. The result is a globally distributed, ACID-compliant relational database that scales effortlessly and maintains guaranteed correctness.

Key features

• Distributed architecture with data automatically replicated across nodes
• ACID transactions across distributed environments
• Horizontal scalability by adding new nodes without downtime or reconfiguration
• Fault tolerance via automatic replication and self-healing
• Continuous read/write operations on all nodes with automatic failover
• MVCC (Multiversion Concurrency Control)
• Serializable isolation for the highest level of transactional isolation
• Raft consensus algorithm for reliable replication and coordination
• RocksDB storage engine optimized for performance and persistence

Best for

• Global transactional applications and multi-region enterprises
• Financial services with fault-tolerant transaction management
• eCommerce platforms
• Gaming backends with low-latency and reliable state management

Pros

• Global consistency for transactions across regions
• Self-healing infrastructure
• Multi-region deployment and data domiciling for compliance
• PostgreSQL compatibility for easy migration
• Flexible deployment models, including self-hosted, managed, and serverless options
• Hotspot detection and balancing

Cons

• Steep learning curve
• Complex initial setup for distributed deployments
• Not ideal for OLAP workloads; optimized for transactional (OLTP) use cases
• Performance degradation with complex joins or analytical queries
• Requires retry logic in applications to handle serialization conflicts

Pricing

• Free - Basic plan
• Paid - Standard and Advanced plans with flexible fees depending on the services

How to choose the right relational database

Choosing the right relational database management system is one of the most strategic decisions in any software or data-driven project. The choice impacts scalability, reliability, performance, and total cost of ownership. The best-fit DBMS depends on several interrelated factors. Primarily, these factors are business size, deployment model, and budget/licensing considerations.

Business size and application needs

Begin by clearly defining your business and application requirements.

For enterprise-level organizations, an advanced RDBMS is essential to manage highly complex data structures, large-scale workloads, and strict demands for reliability, scalability, and compliance. Recommended options include Oracle Database (ideal for mission-critical workloads), Microsoft SQL Server (for organizations using Microsoft technologies and tools such as Power BI and Azure), or PostgreSQL (enterprise-tuned).

For small and medium businesses, which typically manage moderate data volumes (e.g., website content, accounting, inventory, or customer tracking), lightweight and cost-effective databases are usually sufficient. Examples include SQLite (perfect for single-user or embedded applications), MySQL/MariaDB, or PostgreSQL.

Cloud vs on-premises

Your deployment strategy plays a significant role in determining the right system.

Cloud-based projects (e.g., SaaS or web applications) benefit from databases that support elasticity and managed services. Suitable options include PostgreSQL, MySQL/MariaDB, and Google Cloud SQL.

On-premises deployments are preferred when organizations require complete control over configuration, data security, and hardware, or must comply with strict data sovereignty or regulatory requirements. This approach is common in regulated industries or where existing infrastructure is retained. Both open-source and commercial RDBMSs can be on-premises.

Cost, licensing, and support

Cost is often a deciding factor when choosing an RDBMS. Different models offer varying trade-offs:

Open-source systems are ideal for startups, small and medium businesses, and agile teams seeking cost efficiency, flexibility, and vendor independence.

Commercial systems are best suited for mission-critical environments that demand guaranteed support, uptime, compliance, and vendor accountability.

FAQ